Wilkinson Carol L, Gabard-Durnam Laurel J, Kapur Kush, Tager-Flusberg Helen, Levin April R, Nelson Charles A
Division of Developmental Medicine, Boston Children's Hospital, 1 Autumn Street, 6th Floor, Boston, MA 02115.
Division of Developmental Medicine, Boston Children's Hospital.
Neurobiol Lang (Camb). 2020;1(1):33-53. doi: 10.1162/nol_a_00002. Epub 2020 Apr 6.
Language development in children with autism spectrum disorder (ASD) varies greatly among affected individuals and is a strong predictor of later outcomes. Younger siblings of children with ASD have increased risk of ASD, but also language delay. Identifying neural markers of language outcomes in infant siblings could facilitate earlier intervention and improved outcomes. This study aimed to determine whether EEG measures from the first 2-years of life can explain heterogeneity in language development in children at low- and high-risk for ASD, and to determine whether associations between EEG measures and language development are different depending on ASD risk status or later ASD diagnosis. In this prospective longitudinal study EEG measures collected between 3-24 months were used in a multivariate linear regression model to estimate participants' 24-month language development. Individual baseline longitudinal EEG measures included (1) the slope of EEG power across 3-12 months or 3-24 months of life for 6 canonical frequency bands, (2) estimated EEG power at age 6-months for the same frequency bands, and (3) terms representing the interaction between ASD risk status and EEG power measures. Modeled 24-month language scores using EEG data from either the first 2-years (Pearson R = 0.70, 95% CI 0.595-0.783, =1x10) or the first year of life (Pearson R=0.66, 95% CI 0.540-0.761, P=2.5x10) were highly correlated with observed scores. All models included significant interaction effects of risk on EEG measures, suggesting that EEG-language associations are different depending on risk status, and that different brain mechanisms effect language development in low-versus high-risk infants.
自闭症谱系障碍（ASD）儿童的语言发展在受影响个体之间差异很大，并且是后期结果的有力预测指标。ASD儿童的年幼兄弟姐妹患ASD的风险增加，同时也存在语言发育迟缓的情况。识别婴儿兄弟姐妹语言结果的神经标志物有助于早期干预并改善结果。本研究旨在确定生命最初两年的脑电图（EEG）测量是否能够解释ASD低风险和高风险儿童语言发展的异质性，以及确定EEG测量与语言发展之间的关联是否因ASD风险状态或后期ASD诊断而异。在这项前瞻性纵向研究中，将3至24个月期间收集的EEG测量数据用于多元线性回归模型，以估计参与者24个月时的语言发展情况。个体基线纵向EEG测量包括：（1）6个标准频段在3至12个月或3至24个月生命期间EEG功率的斜率；（2）相同频段6个月龄时的估计EEG功率；（3）代表ASD风险状态与EEG功率测量之间相互作用的项。使用生命最初两年（Pearson相关系数R = 0.70，95%置信区间0.595 - 0.783，P = 1×10）或第一年（Pearson相关系数R = 0.66，95%置信区间0.540 - 0.761，P = 2.5×10）的EEG数据建模的24个月语言得分与观察得分高度相关。所有模型都包括风险对EEG测量的显著交互作用，这表明EEG与语言的关联因风险状态而异，并且不同的脑机制影响低风险和高风险婴儿的语言发展。
